Sustainability in the corporate sector: A news textual analysis approach to measuring ESG performance

Mohammad Izzat Raihan Imron

Junior Management Science (JUMS), 2025, vol. 10, issue 2, 369-401

Abstract: Sustainability has become a crucial factor in the financial sector, making the assessment of a company's sustainability performance essential for informed decision-making. Recognizing the media's power to shape public perception of corporate sustainability issues, this study examines the use of news analysis to evaluate companies' performance against Environmental, Social, and Governance (ESG) criteria. Leveraging OpenAI's models, this research parses unstructured data within news articles and introduces a machine learning pipeline to score companies' ESG performance based on their media representation. The study uncovers several key findings: firstly, it demonstrates that a less costly, fine-tuned model can surpass the zero-shot capabilities of a more expensive model in classifying ESG content. Secondly, it identifies discrepancies in media coverage across industries, leading to unequal assessments of companies. Thirdly, it reveals a media tendency to underreport companies' environmental efforts. Finally, the study highlights areas where companies face media criticism, suggesting potential improvements in their ESG practices. These insights contribute to the understanding of how machine learning can assist in the critical evaluation of sustainability in the business domain.

Keywords: ESG; machine learning; natural language processing; news; NLP; sustainability (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:jumsac:320452

DOI: 10.5282/jums/v10i2pp369-401

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